# statmod-package

##### Introduction to the StatMod Package

This package includes a variety of functions for numerical analysis and statistical modelling. The functions are briefly summarized by type of application below.

- Keywords
- documentation

##### Generalized Linear Models

The function `tweedie`

defines a large class of generalized linear model families with power variance functions.
It used in conjunction with the glm function, and widens the class of families that can be fitted.
`qresiduals`

implements randomized quantile residuals for generalized linear models.
The functions
`canonic.digamma`

,
`unitdeviance.digamma`

,
`varfun.digamma`

,
`cumulant.digamma`

,
`d2cumulant.digamma`

,
`meanval.digamma`

and `logmdigamma`

are used to fit double-generalized models, in which a link-linear model is fitted to the dispersion as well as to the mean.
Spefically they are used to fit the dispersion submodel associated with a gamma glm.

##### Growth Curves

`compareGrowthCurves`

,
`compareTwoGrowthCurves`

and
`meanT`

are functions to test for differences between growth curves with repeated measurements on subjects.

##### Limiting Dilution Analysis

The `limdil`

function is used in the analysis of stem cell frequencies.
It implements limiting dilution analysis using complemenary log-log binomial generalized linear model regression, with some improvements on previous programs.

##### Probability Distributions

The functions
`qinvgauss`

,
`dinvgauss`

,
`pinvgauss`

and
`rinvgauss`

provide probability calculations for the inverse Gaussian distribution.
`gauss.quad`

and
`gauss.quad.prob`

compute Gaussian Quadrature with probability distributions.

##### Tests

`hommel.test`

performs Hommel's multiple comparison tests.
`power.fisher.test`

computes the power of Fisher's Exact Test for comparing proportions.
`sage.test`

is a fast approximation to Fisher's exact test for each tag for comparing two Serial Analysis of Gene Expression (SAGE) libraries.
`permp`

computes p-values for permutation tests when the permutations are randomly drawn.

##### Variance Models

`mixedModel2`

,
`mixedModel2Fit`

and
`glmgam.fit`

fit mixed linear models.
`remlscore`

and `remlscoregamma`

fit heteroscedastic and varying dispersion models by REML.
`welding`

is an example data set.

##### Matrix Computations

`matvec`

and `vecmat`

facilitate multiplying matrices by vectors.

*Documentation reproduced from package statmod, version 1.4.2, License: LGPL (>= 2)*